Systems and Methods for Predicting a Required Number of Opened Point of Sale (POS) Stations to Accommodate a Number of Customers

A system for predicting a required number of point of sale (POS) stations to accommodate a number of customers comprising:

• at least one processor;
• and
• a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to:
• analyze image data to determine (i) a set of customer data and (ii) a cart occupancy value associated with the customers,
• generate, utilizing a machine learning (ML) algorithm, a first value based on the set of customer data and the cart occupancy value associated with the customers, the ML algorithm being trained using a plurality of training data including a plurality of training customer data and a plurality of training cart occupancy values,
• determine whether the first value exceeds a second value, and
• responsive to determining that the first value exceeds the second value, generate an alert for transmission to a device indicating that the first value exceeds the second value.

A tangible machine-readable medium comprising instructions for predicting a required number of point of sale (POS) stations to accommodate a number of customers that, when executed, cause a machine to at least:

• analyze image data to determine (i) a set of customer data and (ii) a cart occupancy value associated with the customers;
• generate, utilizing a machine learning (ML) algorithm, a first value based on the set of customer data and the cart occupancy value associated with the customers, the ML algorithm being trained using a plurality of training data including a plurality of training customer data and a plurality of training cart occupancy values;
• determine whether the first value exceeds a second value;
• and
• responsive to determining that the first value exceeds the second value, generate an alert for transmission to a device indicating that the first value exceeds the second value.